Evaluation of the potential index model to predict habitat suitability of forest species: the potential distribution of mountain pine (Pinus uncinata) in the Iberian peninsula

Berlin

2010

S. 133-140

3 Abb., 2 Tab., 40 Lit. Ang.

Artikel aus einer ZeitschriftUnselbständiges Werk

200162101

Characterization of the suitability or potentiality of a territory for forest tree species is an important source of information for forest planning and managing. In this study, we compared a relatively simple methodology to generate potential habitat distribution areas that has been traditionally used in Spain (the potential index model) with a statistical modelling approach (generalized linear model). We modelled the potential distribution of mountain pine (Pinus uncinata) in the Iberian peninsula as a working example. The potential index model generated a map of habitat suitability according to the values of an index of potentiality, whose distribution has usually divided into four categories based on quartiles (from optimum to low suitability). Considering all values of the index of potentiality as presences of mountain pine resulted in a low to moderate degree of agreement between the potential index model and the generalized linear model according to the kappa coefficient. Using the cut-off value of the index of potentiality that maximized the degree of agreement between both modelling approaches resulted in a substantial similarity between the maps of the predicted distribution of mountain pine. This cut-off value did lie in the upper-third quartile of the potential index distribution (high suitability category), and roughly coincided with the upper 30th percentile. The use of statistical techniques, which have proved to be powerful and versatile for species distribution modelling, is recommended. However, the potential index model, together with the adjustments proposed here, could be a reasonably simple methodology to predict the potential distribution of forest tree species that forest managers should take into account when evaluating forestation and afforestation projects.